A Black man in business attire smiles after getting hired. He is seated across from two interviewers who face him.

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As head of talent for Tray.io, Michael Kieran led the implementation of a structured, data-driven hiring process that’s helped the low-code automation company increase employee diversity.

“Using data to make hiring decisions is essential, but certainly not easy,” Kieran said.

Striving for diverse teams and workplaces isn’t only the right thing to do. It also can enhance innovation and financial performance. Data supports that assertion. And step one, according to Fast Company, is to “actively recruit diverse candidates.”

Just in case you needed a reminder — hiring matters. 

“When considering the total costs involved to hire and pay an employee, the cost to retain that person, and then factoring in the potential cost of replacing them, it’s clear that we should treat every hiring decision that we make as a six-figure purchase for the company,” Kieran said. “As we would with a product or service, the decision needs to be made based on objective reasoning and data.”

Kieran and Tray.io use a method called structured hiring.

“At a high level,” Kieran said, “structured hiring is exactly as it sounds. It simply means creating a clear, consistent and structured hiring process and establishing objective evaluation criteria for every role.”

In a recent conversation with ZDNet, Kieran talked about:

  • How and why the company uses a data-driven approach to hiring
  • How the use of data improved the company’s ability to attract and retain talent
  • What other companies might learn from Tray.io’s experience

Below is our email interview. It has been condensed and edited.

What was the company doing before adopting a data-driven approach to hiring?

Michael Kieran: Before implementing this approach, we were doing what most companies across the world do, which is prioritizing previous experience from companies we admire, indexing on the overall dynamic with the hiring team, and at the decision time “using our gut.”

I still believe there is plenty of room for those factors, as they offer very real insight into the potential match between the candidate and employer. But solely resting on resumes, team dynamics, and how enjoyable it would be to “have a beer” with the person is a slippery slope.  

Over time, it creates barriers to entry, breeds homogeneous teams and, ultimately, gives companies a problem-solving disadvantage due to a lack of perspectives in the room. For this reason, we focus on objective data and offset our human tendencies.

Does the data-driven approach extend into the recruitment process?

MK: We certainly use data in our recruitment efforts, but I would liken the data we collect across our recruitment funnel more to a demand-generation machine than the data procurement a company would collect in a buying decision. 

Over the last few years, hiring has been particularly competitive. Most employers have made a significant shift towards prioritizing the employee experience. 

Building a culture and mission that people would like to be a part of and an engaged workforce are no longer differentiators — they are table stakes, and a plethora of companies do them exceptionally well. Candidates have choices!

To attract and interest the most talented people, we continue to iterate on our outbound motion and inbound response — forever pursuing a world-class candidate experience. We are consistently in a “Build > Measure > Learn” loop, always seeking to understand what approaches are working and what can be improved.

What data points do you consider, and which ones are excluded?

MK: In an interview process, we work hard to prioritize objective criteria. In some roles, certain soft skills could be evaluated subjectively. Turning these assessments and opinions into clear data can be challenging. They are the most difficult to bottle and, because of that, where our real work comes in.

Our recruitment team spends considerable time working with hiring managers to truly understand what pain points we are looking to solve with this new employee. Usually, through those conversations, we can better understand why soft skill traits and other subjective criteria can be so important. 

With that understanding, we can design questions, tests, and other objective ways to evaluate a candidate that will give the hiring manager the answers they are looking for without relying on their personal instincts to make the decision.

It’s typically a relief for great hiring managers to help them with this problem. If we can take something difficult to measure and give them a framework they can use to make excellent decisions, they will make better hires and lead stronger teams. 

At the same time, a process and system like this are only as good as your hiring team. When they buy in and commit to the process, commit to objective decision-making, and commit to structured hiring and data being the number one indicator to leverage for a decision, you will have a successful structured hiring mechanism. 

You may have outliers on hiring teams who resist or even refuse to buy into objective hiring. In these situations, it’s not only important to tackle it quickly head-on but to seek to understand why the resistance exists. 

Your potential of uncovering unconscious bias, inconsistent interview questions, or gut decisions will be most high with these outliers.

How much does data influence the final hiring decisions?

MK: In a perfect world, we would interview candidates and have an algorithm — or machine of sorts — that would make all hiring decisions for us with a zero percent margin of error. In reality, people make decisions, and those people and their feelings heavily influence the outcome.  

The final hiring decision is made by the hiring manager. I believe the best hiring managers use every and all data points collected in a review process to reach this decision. They analyze objectively, factor in the potential to succeed, and are certainly aware of the biases they or their team may bring to an assessment — including those in their analysis. 

Ultimately, the best hiring managers see the hiring process as a privilege, a responsibility, and a major decision for the organization. Those that truly see hiring that way welcome objective data to make decisions. 

SEE: Ethical dilemmas in computer science: Why should you care?

How has a data-driven approach to hiring improved diversity?

MK: Our data-driven approach is designed to be objective and actively remove bias from the hiring process, making teams more diverse — from their backgrounds and past experiences to their skills, education, and more. 

With our hiring approach, we see the potential in candidates from underrepresented groups sometimes overlooked for more subjective reasons, such as where they went to school. 

Our HR and talent departments regularly hold internal training sessions for general employees and management to cover topics such as subconscious bias, interviewer training, and non-harassment. 

To ensure equity for diverse candidates during the hiring process, we’ve also implemented an augmented writing platform that scans job descriptions to ensure our language is geared toward equity without subconscious bias. 

How can companies use the insights Tray.io has learned?

MK: While resumes and previous experience are great to include in an assessment and provide a compelling story about someone, they are really only evidence of what someone has done in the past. … 

A very simple and practical way to map potential is to put a candidate’s trajectory on a line graph on a scale of 1-10. Where they are today is important, but where they will be in 12 months is what’s most important. 

For example, would you rather hire someone who is an eight today and will remain an eight over time or someone that is a seven today but will be a nine in a year? 

Often, that seven’s experience profile is based on a lack of opportunity. If you are the company and leader that gives them that opportunity, you have yourself a missionary. 

As more companies begin to recognize this, they can help individuals in underrepresented groups build careers, break economic cycles, and truly impact lives.

To implement their own data-driven, objective hiring process, companies must first evaluate who they are as a company, including clearly defining their culture and core values — and then hone in and define the specific criteria needed to be successful in each role at the company.

As with any change management, implementing structured hiring can fall into three steps. 

First, build trust by asking and answering, “Why are we doing this?” Second, create clarity. What are the expectations and results of doing this? Third, execute and drive results. …

Ensuring teams are diverse and breaking down barriers also allows organizations to leave an impactful legacy of their own that helps to attract and retain top talent.

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